{"id":"W3124915739","doi":"10.29173/alr284","title":"Promoting Transparency While Protecting Privacy in Open Government in Canada","year":2015,"lang":"en","type":"article","venue":"Alberta Law Review","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Transparency (behavior); Open government; Information privacy; Internet privacy; Government (linguistics); Personally identifiable information; Context (archaeology); Open data; Privacy policy; Privacy by Design; Balance (ability); Business; Privacy law; Public relations; Law; Political science; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01893841,0.0003264069,0.0007685046,0.003100205,0.01682891,0.01612148,0.002610751,0.006393953,0.002492172],"category_scores_gemma":[0.03455409,0.0006139773,0.0007760219,0.006388039,0.01773597,0.004619358,0.00571757,0.007484097,0.000172992],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1458646,"about_ca_system_score_gemma":0.4051086,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9858004,"about_ca_topic_score_gemma":0.9899037,"domain_scores_codex":[0.969541,0.007380141,0.001009482,0.001330263,0.01267677,0.008062419],"domain_scores_gemma":[0.9656677,0.01572855,0.001882286,0.001382837,0.01230031,0.003038335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002834816,0.00002971558,0.002595501,0.0003841295,0.00004858767,0.0003419812,0.005550128,0.001347832,0.0002653714,0.9275718,0.03177528,0.03006125],"study_design_scores_gemma":[0.0001491649,0.00006186323,0.02300514,0.003015332,0.0002552152,0.0002428832,0.01084862,0.002274619,0.001005662,0.2724285,0.6864998,0.0002131039],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0695046,0.1081191,0.008905623,0.4145849,0.001485674,0.0004255044,0.0004494419,0.0001091899,0.3964159],"genre_scores_gemma":[0.8655973,0.04814538,0.005562861,0.05906899,0.0005882474,0.0001250398,0.0001310831,0.00003992125,0.02074119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8541355,"threshold_uncertainty_score":0.990676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07439652247766318,"score_gpt":0.3211564559779279,"score_spread":0.2467599335002647,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}